Influence of metal nanoparticles synthesized by microorganisms upon soil-borne microscopic fungus Aspergillus terreus K-8 was studied. It was established that the metal nanoparticles synthesized by microorganisms affect the enzymatic activity of the studied culture. Silver nanoparticles lead to a decrease in cellulase activity and completely suppress the amylase activity of the fungus, while copper nanoparticles completely inhibit the activity of both the cellulase complex and amylase. The obtained results imply that the large-scale use of silver and copper nanoparticles may disrupt biological processes in the soil and cause change in the physiological and biochemical state of soil-borne microorganisms as well.

The aim of the research is to study the comparison between (ARIMA) Auto Regressive Integrated Moving Average and(ANNs) Artificial Neural Networks models and to select the best one for prediction the monthly relative humidity values depending upon the standard errors between estimated and observe values . It has been noted that both can be used for estimation and the best on among is (ANNs) as the values (MAE,RMSE, R2) is )0.036816,0.0466,0.91) respectively for the best formula for model (ARIMA) (6,0,2)(6,0,1) whereas the values of estimates relative to model (ANNs) for the best formula (5,5,1) is (0.0109, 0.0139 ,0.991) respectively. so that model (ANNs) is superior than (ARIMA) in a such evaluation.

In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

In this paper a new method is proposed to perform the N-Radon orthogonal frequency division multiplexing (OFDM), which are equivalent to 4-quadrature amplitude modulation (QAM), 16-QAM, 64-QAM, 256-QAM, ... etc. in spectral efficiency. This non conventional method is proposed in order to reduce the constellation energy and increase spectral efficiency. The proposed method gives a significant improvement in Bit Error Rate performance, and keeps bandwidth efficiency and spectrum shape as good as conventional Fast Fourier Transform based OFDM. The new structure was tested and compared with conventional OFDM for Additive White Gaussian Noise, flat, and multi-path selective fading channels. Simulation tests were generated for different channels

The survival analysis is one of the modern methods of analysis that is based on the fact that the dependent variable represents time until the event concerned in the study. There are many survival models that deal with the impact of explanatory factors on the likelihood of survival, including the models proposed by the world, David Cox, one of the most important and common models of survival, where it consists of two functions, one of which is a parametric function that does not depend on the survival time and the other a nonparametric function that depends on times of survival, which the Cox model is defined as a semi parametric model, The set of parametric models that depend on the time-to-event distribution parameters such as

ABSTRUCT

In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error          ( λ ) in the model (SPSEM), estimated  the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo

This study looks into the many methods that are used in the risk assessment procedure that is used in the construction industry nowadays. As a result of the slow adoption of novel assessment methods, professionals frequently resort to strategies that have previously been validated as being successful. When it comes to risk assessment, having a precise analytical tool that uses the cost of risk as a measurement and draws on the knowledge of professionals could potentially assist bridge the gap between theory and practice. This step will examine relevant literature, sort articles according to their published year, and identify domains and qualities. Consequently, the most significant findings have been presented in a manne